ST4.1

EDI
Space Weather Prediction of Solar Wind Transients in the Heliosphere

Coronal Mass Ejections and their interplanetary counterparts (ICMEs), the associated shocks, the high-speed streams of solar wind from corotating interaction regions (CIRs), and the solar energetic particles (SEPs) are the main drivers of the heliospheric variability. The corresponding geospace disturbances affect a wide range of technological systems in space and on ground, as well as human health. Therefore, the prediction of their arrival and impact is extremely important for the modern space-exploration and electronics-dependent society.

Significant efforts have been made in the past decade to develop and improve the prediction capabilities, through both state-of-the art observations and modelling. Although significant progress has been made, many new challenges have been revealed. We are limited in obtaining reliable observation-based input for the models, tracking solar wind transients throughout the heliosphere and reliably evaluating prediction models. These challenges can be tackled by exploiting and improving our existing capabilities, as well as using the out-of-the-box thinking and break from the traditional methods.

This session is devoted to provide the overview of the current state of the space weather prediction of the arrival time and impact of various solar wind transients and to introduce new and promising observational and modelling capabilities.

We solicit abstracts on observational and modelling efforts, as well as space weather prediction evaluation. With the overview of our current capabilities and possible future prospects we aim to highlight guidelines to the general direction of the future scientific efforts, as well as space-mission planning.

Convener: Evangelos PaourisECSECS | Co-conveners: Mateja DumbovicECSECS, Tanja AmerstorferECSECS, Dario Del Moro
Presentations
| Wed, 25 May, 13:20–15:40 (CEST)
 
Room L1

Presentations: Wed, 25 May | Room L1

Chairpersons: Evangelos Paouris, Mateja Dumbovic
13:20–13:30
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EGU22-10831
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ECS
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solicited
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Virtual presentation
Erika Palmerio

Coronal mass ejections (CMEs) and solar energetic particles (SEPs) are manifestations of the dynamic and explosive nature of solar activity and major drivers of space weather events. They often occur in concert, especially in the case of large and fast CMEs that are associated with strong flares and that are able to accelerate SEPs at the shocks ahead of them. Modelling efforts that aim to forecast and mitigate the effects of these solar phenomena range from empirical to analytical to numerical. Although the primary focus of space weather forecasts is naturally on Earth, the increased amount of heliospheric and planetary missions launched in the past ~15 years has provided new opportunities for CME and SEP measurements at other locations in the inner solar system. This has resulted in the possibility to test space weather forecasting models at multiple locations well separated in both heliocentric distance and longitude within the same event, which in turn represents a novel way to benchmark and validate the present capabilities.

In this presentation, we will first briefly review the current status of CME and SEP space weather forecasting, with particular attention given to the main challenges to overcome for advancing predictions. We will then present a few examples of CME and SEP events that were detected in situ at multiple locations in the inner heliosphere and show forecasting—or actually hindcasting—results for each of them. Finally, we will conclude by addressing possible future improvements that take advantage of model validation via multi-spacecraft measurements.

How to cite: Palmerio, E.: Space weather predictions of CMEs and SEPs through the inner heliosphere, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10831, https://doi.org/10.5194/egusphere-egu22-10831, 2022.

13:30–13:36
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EGU22-3857
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ECS
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On-site presentation
Karmen Martinic, Mateja Dumbovic, Manuela Temmer, Astrid Veronig, and Bojan Vrsnak

The configuration of the interplanetary magnetic field and features of the related ambient solar wind in the ecliptic and meridional plane are different. Therefore, one can expect that the orientation of the flux rope axis of a coronal mass ejection (CME) influences the propagation of the CME itself. However, the determination of the CME orientation remains a challenging task to perform. This study aims to provide a reference to different CME orientation determination methods in the near-Sun environment. Also, it aims to investigate the non-radial flow in the sheath region of the interplanetary CME (ICME) in order to provide the first proxy to relate the ICME orientation with its propagation. We investigated 22 isolated CME-ICME events in the period 2008-2015. We first determined the CME orientation in the near-Sun environment using a 3D reconstruction of the CME with the graduated cylindrical shell (GCS) model applied to coronagraphic images provided by the STEREO and SOHO missions. The CME orientation in the near-Sun environment was determined using an ellipse fitting technique to the CME outer front as determined from the SOHO/LASCO coronagraph. In the near-Earth environment, we obtained the orientation of the corresponding ICME using in-situ plasma and field data and also investigated the non-radial flow in its sheath region. The ability of GCS and ellipse fitting to determine the CME orientation is found to be limited to only distinguishing between the high or low inclination of the events. Most of the CME-ICME pairs under investigation were found to be characterized by a low inclination, and regardless of whether their inclination was high or low, the CME-ICME pairs maintained their inclination during interplanetary propagation. The observed non-radial flows in the sheath region show a greater y-direction to z-direction flow ratio for low-inclination events which suggests that there is a connection between the orientation and propagation of the observed CME-ICME pairs.

How to cite: Martinic, K., Dumbovic, M., Temmer, M., Veronig, A., and Vrsnak, B.: Determination of CME orientation and consequences for their propagation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3857, https://doi.org/10.5194/egusphere-egu22-3857, 2022.

13:36–13:42
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EGU22-2968
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ECS
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On-site presentation
Mohamed Nedal, Heba Shalaby, and Ayman Mahrous

Predicting the arrival time of Coronal Mass Ejections (CME) and the strength of their geomagnetic storms at Earth is crucial in space operations and essential to avoid losing our space instruments and not to risk our astronauts’ lives in space. Besides, protecting the power grids and pipelines on the ground from the side effects of geomagnetic storms. We contribute to this matter by implementing Neural Network (NN) models to predict the CME transit time and the minimum value of the Disturbed storm time (Dst) index of the associated geomagnetic storm.

For the first time, we employed the planets' ephemeris as input features. Taking the CME properties (angular width, linear speed, speed at 20 solar radii, measurement position angle, latitude, and longitude), the solar wind and plasma parameters (the differential speed between the CME and the solar wind, the average interplanetary magnetic field with its 3D components, proton density and plasma temperature, speed in 3D components, dynamic pressure, electric field, plasma beta parameter, Mach number, and magnetosonic Mach number), and the planets' ephemeris in the solar system (distance from the Sun, latitude, and longitude) as inputs, we performed a grid of NNs to predict not only the CME transit time but also the minimum disturbed storm time (Dst) index of the associated geomagnetic storm.

We proposed the new Best-of-the-Best (BOB) approach to optimize the NN hyperparameters using the GridSearch method in Python. We assembled our dataset from (Gopalswamy et al., 2010), (Micha lek et al., 2004), and (Richardson and Cane, 2010) with a total of 230 events between 1997 and 2020. This is the largest dataset of CME-ICME pairs along with solar wind indices and planets locations in the solar system so far.

Remarkably, for the given dataset, the best set of input features for predicting the CME transit time was the CME features and the planets' ephemeris, while for predicting the Dst index were the top correlated features, with a Mean Absolute Error (MAE) of 13.54 hr and 35.57 nT, respectively. More details are described in the manuscript. 

How to cite: Nedal, M., Shalaby, H., and Mahrous, A.: Predicting the Transit Time and Geo-effectiveness of Coronal Mass Ejections using Neural Networks, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2968, https://doi.org/10.5194/egusphere-egu22-2968, 2022.

13:42–13:48
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EGU22-8887
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ECS
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Virtual presentation
Ajay Tiwari, Enrico Camporeale, Dario Del Moro, Raffaello Foldes, Gianluca Napoletano, Giancarlo de Gasperis, and Jannis Teunissen

Coronal mass ejections are one of the most significant drivers of space weather. The ToA predictions along with the Arrival speed of the CMEs are one of the crucial pieces of information for preparing for the possible geomagnetic storms. Geomagnetic storms can have adverse effects on several key components of modern society e.g. communications and electrical grids. The development of many machine learning methods provides us with the opportunity to use these tools in space weather applications. There have been several studies using machine learning methods for ToA predictions. In this study, we present an interactive dashboard to apply several machine learning methods (regression models) to test on the several CME databases used in the community. We also use this opportunity to benchmark various CME databases for TOA and CME arrival speed predictions. We also welcome the community to use this interactive dashboard as a tool to learn about machine learning.

How to cite: Tiwari, A., Camporeale, E., Del Moro, D., Foldes, R., Napoletano, G., de Gasperis, G., and Teunissen, J.: CME-learn: An interactive playground to benchmark CME databases for the time of arrival (ToA) prediction for using machine learning methods., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8887, https://doi.org/10.5194/egusphere-egu22-8887, 2022.

13:48–13:54
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EGU22-11702
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ECS
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Virtual presentation
Evangelos Paouris and Angelos Vourlidas

The estimation of the Coronal Mass Ejection (CME) arrival at Earth is an open issue in the field of Space Weather. We present a new near real-time algorithm based on heliospheric imaging (HI) observations of the CME front as a function of time. First, we transform the front elongation angle into radial distance using basic stereoscopic techniques (i.e. fixed-phi, harmonic mean and self-similar expansion). Then we adopt the assumptions that (1) CME accelerate (or decelerate) from the Sun up to some distance and (2) they move with a constant speed past that distance. This “two-phase kinematics” behavior forms the core of our algorithm. The resulting kinematic profiles provide estimates of the CME Time-of-Arrival (ToA) and Speed-on-Arrival (SoA) at 1 AU. This new tool is tested on a sample of CMEs where stereoscopic views were possible, from the STEREO-A and -B HIs were available. The algorithm is promising with predictions for the ToA of CMEs of the order of ±1 hour and for SoA of ±100 km/s. Our approach is in preparation for a possible future combination of HI data from missions at L5. We will test our method further for cases beyond the 1 AU studying ICMEs which has been spotted also on Mars (1.52 AUs).

How to cite: Paouris, E. and Vourlidas, A.: A potential near real-time algorithm for CME propagation utilizing heliospheric imaging observations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11702, https://doi.org/10.5194/egusphere-egu22-11702, 2022.

13:54–14:00
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EGU22-9594
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ECS
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Presentation form not yet defined
Galina Chikunova, Tatiana Podladchikova, Karin Dissauer, and Astrid Veronig

Coronal dimmings are regions in the solar corona that represent a sudden decrease of the coronal EUV and SXR emission, which is interpreted as a density depletion caused by the evacuation of plasma due to the CME eruption. Distinct relations have been established between coronal dimming parameters (intensity, area, magnetic flux) and key characteristics (mass, speed) of the associated CMEs by combining coronal and coronagraphic observations from different viewpoints in the heliosphere   (Dissauer et al. 2019, Chikunova et al. 2020).

In this contribution, we study whether coronal dimmings can be used to indicate possible deflections of CMEs close to the Sun and to identify their propagation direction. We present a set of detailed case studies where, by using simultaneous observations from the SDO and STEREO satellites, we track both the evolution of the coronal dimmings and the CME properties with respect to their directions. Our findings suggest that the direction of growth of the coronal dimming region and the evolution of the dimming intensity are related to the initial direction of the CME and also reflect various changes in its evolution, indicating deflection and/or interaction with surrounding active regions. These findings are important in better constraining CME evolution and direction close to the Sun and its further connection toward interplanetary space.

How to cite: Chikunova, G., Podladchikova, T., Dissauer, K., and Veronig, A.: Coronal dimmings as indicators of the CME  evolution close to the Sun, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9594, https://doi.org/10.5194/egusphere-egu22-9594, 2022.

14:00–14:06
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EGU22-11485
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ECS
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Virtual presentation
Alexander James, David Williams, and Jennifer O'Kane

Aims: Working towards improved space weather predictions, we aim to quantify how the critical height at which the torus instability drives coronal mass ejections (CMEs) varies over time in a sample of solar active regions.

Methods: We model the coronal magnetic fields of 43 active regions and quantify the critical height at their central polarity inversion lines throughout their observed lifetimes. We then compare these heights to the changing magnetic flux at the photospheric boundary and identify CMEs in these regions.

Results: We find higher rates of CMEs per unit time during phases when the critical height is falling rather than rising, and when magnetic flux is increasing rather than decreasing. Furthermore, we support and extend the results of previous studies by demonstrating that the critical height in active regions is generally proportional to the separation of their magnetic polarities through time.

How to cite: James, A., Williams, D., and O'Kane, J.: Evolution of the critical torus instability height and CME likelihood in solar active regions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11485, https://doi.org/10.5194/egusphere-egu22-11485, 2022.

14:06–14:12
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EGU22-8908
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On-site presentation
Eleanna Asvestari, Tobias Rindlisbacher, Jens Pomoell, and Emilia Kilpua

Accurate reconstruction of the magnetic field topology of coronal mass ejections (CMEs) is essential in space weather forecasting and thus in the spotlight of modelling efforts. The spheromak, a force-free, axisymmetric configuration within which plasma is confined by a twisted magnetic field that fills a spherical volume, is at the moment the most commonly employed flux rope model, which has entered numerous published event studies. Despite its widespread application, not much attention has been paid to the spheromak tilting, which not only affects the spheromak's orientation in the modelling domain, but also its direction of propagation. This can lead to implications when comparing simulation output to observations. The tilting of the spheromak occurs when its magnetic moment is at an angle with the ambient magnetic field. In this case a torque is exerted on the spheromak, forcing it to rotate, so that its magnetic moment aligns to the ambient magnetic field. In our study we used EUHFORIA to investigate the spheromak tilting under different conditions. We developed a method to monitor the spheromak's position and orientation in the EUHFORIA simulation output, and we quantified how the spheromak's total drift and rotation angle depend on various input parameters. We find that the spheromak experienced tilting in all studied scenarios resulting often in a significantly changed orientation to that which it had during insertion. We emphasize that in space weather modelling it is crucial to take into consideration the spheromak tilting, in particular when comparing the model output to observations.

How to cite: Asvestari, E., Rindlisbacher, T., Pomoell, J., and Kilpua, E.: The impact of the spheromak tilting in space weather modelling, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8908, https://doi.org/10.5194/egusphere-egu22-8908, 2022.

14:12–14:18
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EGU22-5020
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ECS
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On-site presentation
Tinatin Baratashvili, Stefaan Poedts, and Christine Verbeke

Coronal Mass Ejections (CMEs) are the main drivers of interplanetary shocks and space weather disturbances. One of the key parameters that determine the geo-effectiveness of the CME is its internal magnetic configuration. Strong CMEs directed towards Earth can have a severe impact on our planet and their prediction can mitigate possible damages. 

 

The novel heliospheric model Icarus, which is implemented within the framework of MPI-AMRVAC (Xia et al., 2018) introduces new capabilities to model the heliospheric wind and real CME events. Advanced techniques, such as adaptive mesh refinement and grid stretching are implemented. By imposing these techniques, we avoid cell deformation in the domain and only the necessary/desired areas are refined to higher spatial resolutions (and coarsened again when the high resolution is no longer necessary, e.g. behind a travelling shock wave). The refinement and coarsening conditions are controlled by the user. These techniques result in optimised computer memory usage and a significant speed-up, which is crucial for forecasting purposes. 

 

In order to model the magnetic field of the CME and its interaction with the solar wind, the Gibson and Low model is implemented in Icarus. In order to assess the ICARUS model capabilities to predict the solar wind conditions in the heliosphere, especially at L1, we consider a real CME event.  Further, we perform a comparison of the results of the existing Linear Force-Free Spheromak model and the new advanced model. To perform the full comparison we compare the time series data at L1 and other satellites, while we also monitor the time that simulations require to model the heliospheric wind and CME events. 

 

The solution mesh refinement is applied to the CMEs in order to model its arrival time and interior magnetic field better. To analyse the results, the radial, longitudinal and latitudinal components of the magnetic field are compared to the original EUHFORIA simulations and the observed data. As a result, the new magnetized model gives an opportunity to model the CME better and a bigger range of parameters to investigate to model the event as accurately as possible.  

 

This research has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870405 (EUHFORIA 2.0).

How to cite: Baratashvili, T., Poedts, S., and Verbeke, C.: The effect of AMR on the advanced magnetized CME model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5020, https://doi.org/10.5194/egusphere-egu22-5020, 2022.

14:18–14:24
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EGU22-9162
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On-site presentation
Tanja Amerstorfer, Maike Bauer, Christian Möstl, Luke Barnard, Pete Riley, Andreas J. Weiss, and Martin A. Reiss

We present first results of a case study on a CME from October 2021 that was in situ detected by BepiColombo, Solar Orbiter, DSCOVR and STEREO-A, whose Heliospheric Imagers (HI) additionally observed the event remotely. The latter observations are used to model the evolution of the CME through the inner heliosphere using the CME propagation model ELlipse Evolution based on HI (ELEvoHI). ELEvoHI assumes a drag-based interaction of the CME-sheath with the solar wind and allows it to deform according to local drag regimes. The ambient solar wind is provided by the time-dependent HelioMAS/HUXt model. Using the arrivals at the four different spacecraft we are able to assess the ability of ELEvoHI to model the evolution of the shape of this CME.

How to cite: Amerstorfer, T., Bauer, M., Möstl, C., Barnard, L., Riley, P., Weiss, A. J., and Reiss, M. A.: Drag-based deformation of a multi-point CME event, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9162, https://doi.org/10.5194/egusphere-egu22-9162, 2022.

14:24–14:30
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EGU22-3816
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On-site presentation
Jaša Čalogović, Mateja Dumbović, Bojan Vršnak, Manuela Temmer, and Astrid Veronig

Drag-Based Ensemble Model (DBEM) is a probabilistic model for heliospheric propagation of Coronal Mass Ejections (CMEs) that predicts the CME hit chance, most probable arrival times and speeds, quantify the prediction uncertainties and calculate the confidence intervals. DBEM is based on the 2D analytical Drag-based Model (DBM) with very short computational time. By using CME cone geometry with flattening DBM calculates the CME arrival time and speed at Earth or any other given target in the solar system. DBEM considers the variability of model input parameters by making an ensemble of n different input parameters to obtain the distribution and significance of the DBM results. As an important tool for space weather forecasters, DBM/DBEM web application is integrated as one of the ESA Space Situational Awareness portal services (https://swe.ssa.esa.int/current-space-weather). Important requirement to perform DBM calculations is to assume that two input parameters namely background solar wind speed and the drag parameter γ are constant in order to have the analytical solution and fast computational times. However, this assumption is not always valid in more complex heliospheric conditions. Thus, to further increase the accuracy of CME propagation forecast we developed the new DBEMv4 version that calculates CME propagation in more steps with variable solar wind speeds. This allows also to employ as DBEMv4 input the dynamic solar wind data in real-time taken from simple persistence model under consideration of the CME propagation direction.

How to cite: Čalogović, J., Dumbović, M., Vršnak, B., Temmer, M., and Veronig, A.: Drag-Based Ensemble Model (DBEMv4) with variable solar wind speed input, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3816, https://doi.org/10.5194/egusphere-egu22-3816, 2022.

Coffee break
Chairpersons: Tanja Amerstorfer, Dario Del Moro
15:10–15:16
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EGU22-10472
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ECS
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On-site presentation
Nishtha Sachdeva, Gabor Toth, Ward Manchester, Bart van der Holst, Zhenguang Huang, and Carl Henney

The first step towards reliable prediction of the impact of solar transients that drive space weather is to accurately model the background solar wind into which these transients propagate. Uncertainties in the plasma environment into which CMEs propagate can lead to significant errors in time of arrival and impact prediction which is important for technology that humans are routinely dependent on as well as space-based explorations.

We use the physics-based 3D extended MHD Alfven Wave Solar atmosphere Model (AWSoM) within the Space Weather Modeling Framework (SWMF) developed at the University of Michigan to model the solar wind conditions during periods of high activity that include many strong solar transient events. These modeling efforts are validated by both in-situ and remote observations including EUV observations in the low corona from STEREO-A/B and SDO-AIA as well as plasma parameters at L1 from the OMNI database. AWSoM is driven by observations of the photospheric magnetic field. We use the ADAPT magnetic field maps that model the evolution of the observed magnetic field on the solar surface using physical processes like flux-transport, supergranulation and meridional flows. Our results show how our solar corona model behaves when driven by different data products like GONG and HMI observations.

In addition to the input magnetograms, the results also depend on model parameters. AWSoM is a self-consistent physics-based model with only a few free parameters. In our NSF funded Space Weather with Quantified Uncertainty (SWQU) project we systematically study the uncertainty quantification associated with various model inputs and parameters. We find that during periods of higher solar activity the Poynting flux parameter at the inner boundary needs to be adjusted to match the observations well to provide correct initial conditions for CME propagation. This work is in preparation for simulating CMEs launched from the Sun and propagating into correct solar wind background in order to achieve accurate and reliable space weather modeling and prediction.

How to cite: Sachdeva, N., Toth, G., Manchester, W., van der Holst, B., Huang, Z., and Henney, C.: Modeling solar wind background for CME propagation using the Alfven Wave Solar atmosphere Model (AWSoM), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10472, https://doi.org/10.5194/egusphere-egu22-10472, 2022.

15:16–15:22
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EGU22-4063
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ECS
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On-site presentation
Daniel Milosic, Manuela Temmer, Stephan Heinemann, Tatiana Podladchikova, Astrid Veronig, and Bojan Vršnak

The empirical solar wind forecast (ESWF) model is an ESA service to forecast the solar wind speed at Earth with 4 days lead time. The model uses a simple empirical relation between the area of coronal holes (CHs) as measured in meridional slices in EUV at the Sun and the in-situ measured solar wind speed at 1 AU (Vršnak, Temmer, Veronig, 2007). The relation has the drawback that Gaussian type speed profiles are produced as the CH rotates in and out of the meridional slice. With adaptations to the ESWF algorithm we aim to improve the precision of the ESWF speed profile by implementing compression and rarefaction effects occurring between SW streams of different velocities in the interplanetary space. By considering the propagation times for plasma parcels between the Sun and Earth and their interactions, we achieve the asymmetrical shape of the speed profile that is characteristic of high-speed streams (HSS). We present a statistical analysis for the period 2012 - 2019 showing that our adaptions improve the ability to predict HSS speed profiles as well as smaller structures with higher precision.

How to cite: Milosic, D., Temmer, M., Heinemann, S., Podladchikova, T., Veronig, A., and Vršnak, B.: Improving the Empirical Solar Wind Forecast (ESWF) model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4063, https://doi.org/10.5194/egusphere-egu22-4063, 2022.

15:22–15:28
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EGU22-4595
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On-site presentation
Benjamin Grison, Nicole Cornilleau-Wehrlin, Karine Bocchialini, and Brigitte Schmieder

Bocchialini et al. (2018) showed that among the 28 frontside halo coronal mass ejections (CMEs) with a visible source seen on the Sun in 2002, 21 are unambiguously associated with sudden storm commencements (SSCs). Based on velocity comparisons (LASCO, L1, and ballistic velocities), we look for association between these 28 halo CMEs and shock-like discontinuities observed in solar wind and interplanetary magnetic field (IMF) observations at L1. Geoeffectivity is tested on Dst, am, PCN, and auroral indices responses.

The present work complements the Boochialini's study by analysing systematically all the 28 halo CMEs, including the seven halos CMEs not associated with SSCs. Source locations, potential L1 signatures and geoeffectivity of these seven halo CMEs provide an overview of the properties related to halo CMEs in 2002, complementing Boccialini's et al. results. None of the discontinuities possibly associated to each of the seven halo CMEs corresponds to a clear ICME signature, based on our observations and on existing catalogs, showing that the central regions of the halo CMEs are not passing L1.

From the L1 observations of frontside CME halos observed in 2002, we conclude that halo CMEs not associated with SSCs in 2002 are non-geoeffective. We also note that all halo CMEs observed in 2002 and associated with ICMEs or magnetic clouds at L1 are also associated with SSCs. lders. The work leading to this paper has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870437 for the SafeSpace (Radiation Belt Environmental Indicators for the Safety of Space Assets) project.

How to cite: Grison, B., Cornilleau-Wehrlin, N., Bocchialini, K., and Schmieder, B.: L1 observations and geoeffectivity consecutive to the frontside halo coronal mass ejections (CMEs) of year 2002, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4595, https://doi.org/10.5194/egusphere-egu22-4595, 2022.

15:28–15:34
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EGU22-8660
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ECS
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Virtual presentation
Simona Nitti, Tatiana Podladchikova, Astrid M. M. Veronig, Stefan Hofmeister, Giuliana Verbanac, and Mario Bandić

Coronal holes (CHs) are the source of high-speed solar wind streams (HSSs), which interact with the slow solar wind and form corotating interaction regions (CIRs) in the heliosphere. These high-speed streams and their associated structures influence the geomagnetic activity, causing recurrent geomagnetic storms. The propagation time of solar wind from Sun to Earth is about 1–5 days, creating a natural lead-time for early warning. However, the magnetic structure of an interplanetary perturbation, in particular the southward component Bz of the interplanetary magnetic field (IMF), driving the storm, cannot be determined from solar observations yet, which strongly limits the possibility of storm forecast several days in advance. Current approaches to quantitative storm predictions are often limited to a short-term forecast based on measurements of IMF and solar wind at the Lagrange point L1, which is possible due to the 1-hour difference in the propagation time from L1 to Earth between the radio signal and solar wind.

In this study, we focus on predictions of CIR-driven geomagnetic storms from solar observations with the aim of increasing the warning lead-time from hours to days. We develop a prediction technique of geomagnetic storms using coronal holes at the Sun as well as corresponding solar magnetic field data (cf. Vrsnak et al. 2007). The method is based on establishing empirical relations between the time-series of coronal hole areas on the Sun derived from SDO/AIA images and the solar wind speed at L1; between remote-sensing magnetic field maps of the solar photosphere and that measured in-situ at L1, and finally between coronal hole areas, corresponding magnetic field at Sun and geomagnetic Dst and Kp indices. We demonstrate that the inward/outward direction of the magnetic field originating from the base of a coronal hole is preserved in more than 80% of cases when compared to the related magnetic field measured at Earth. This opens the possibility to use the magnetic field derived from solar observations instead of that at L1. Additionally, to improve the predictions for which we need to derive the Bz component, we analyze the Russel-McPherron effect, which reflects the change of the Bz component and the associated geomagnetic activity through the seasons. The approach proposed in this study for forecasting the Dst/Kp indices makes use of the Gaussian Process Regression, a non-parametric Bayesian model, suitable in case of limited available data, flexible non-linear problems and known prior information about the output (e.g. periodicity). Testing the developed forecasting technique for the whole SDO period 2010-2020, we obtained that the correlation coefficient between the predicted and observed Dst (Kp) index reaches r = 0.68/0.73 (0.67/0.76), for coronal holes having the positive/negative polarity on the Sun. These results demonstrate that the proposed technique opens a possibility to predict CIR-driven geomagnetic storms from solar observations resulting in the extension of the lead time from hours up to several days, which is highly important for warnings of the space weather conditions in the near-Earth environment and other space weather applications.

How to cite: Nitti, S., Podladchikova, T., M. Veronig, A. M., Hofmeister, S., Verbanac, G., and Bandić, M.: Geomagnetic storms forecasting from solar coronal holes, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8660, https://doi.org/10.5194/egusphere-egu22-8660, 2022.

15:34–15:40
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EGU22-11848
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ECS
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Virtual presentation
Mikhail Fridman, Olga Khabarova, Timofey Sagitov, and Roman Kislov
The number of current sheets observed at 1 AU depends on the corresponding type of the solar wind plasma flow or stream in which current sheets occur. Prior studies have shown that the maximum of the current sheet rate is detected in turbulent and hot flows and streams such as corotating/stream interaction regions (CIRs/SIRs) and the coronal mass ejection (ICME) sheath (Khabarova et al. JGR, 2021,  https://doi.org/10.1029/2020JA029099).  It is also known that the number of current sheets per hour begins to rise several hours before the arrival of potentially geoeffective CIRs/SIRs and ICMEs. This effect has been interpreted in literature as a crossing of so-called magnetic cavities filled with coherent structures (Khabarova et al. Sp Sci Rev. 2021, https://doi.org/10.1007/s11214-021-00814-x).
On the other hand, it is known that geomagnetic storms are preceded by ULF variations in the interplanetary magnetic field and solar wind density. We show that such ULF variations are associated with crossings of magnetic islands and current sheets inside magnetic cavities formed in front of geoeffective high-speed streams and flows.
A statistical analysis of the occurrence of current sheets prior to geomagnetic storms has been carried out employing the multi-year database of current sheets at 1 AU for 2011-2013 (see https://csdb.izmiran.ru) . 43 geomagnetic storms with Dst index lower than  -50nT were detected during that period . The results show that there is an 80% increase in the number of current sheets before a geomagnetic storm commencement with a 10-hour advance time, on average. Therefore, current sheets can potentially be used as geomagnetic storm precursors.
A mid-term geomagnetic storm forecast technique using a Recurrent Neural Network for an automatic pattern search is proposed, based on this phenomenon. The minute data of the solar wind density, the number of current sheets, and the window Fourier transform results are taken as input data. Examples of the mid-term prognosis of geomagnetic storms are presented.

How to cite: Fridman, M., Khabarova, O., Sagitov, T., and Kislov, R.: Current sheets in front of geoeffective streams and flows as precursors of geomagnetic storms, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11848, https://doi.org/10.5194/egusphere-egu22-11848, 2022.